InterviewIQ

Inspiration

Interviewing can be stressful, and practicing on your own can feel aimless. We wanted to create a tool that not only generates realistic interview questions but also gives actionable feedback, helping candidates improve quickly and confidently.

What it does

Our app, InterviewIQ, simulates an interview experience. Users can:

Practice answering interview questions based off an uploaded job description generated by Claude
Record their answers via microphone.
Get immediate analysis by Claude of their responses and scores based on categories, including -- -confidence, structure, and relevance to the job.
Track their progress over multiple sessions to see improvement.

How we built it

Frontend: React with TypeScript and TailwindCSS for a fast, responsive UI.

Backend: FastAPI with PostgreSQL for session and user data management.

AI: Claude API to generate interview questions and analyze user responses.

Audio processing: Faster Whisper (based on OpenAI’s Whisper model) to transcribe user responses from recordings.

We integrated these components into a seamless flow where a user can upload a new job profile, answer questions, and receive feedback in moments.

Challenges we ran into

The time limit we were given meant we had to rush through the code without being able to tune everything as we went. Therefore, we ran into a few bugs and errors at the end that prevented our application from properly functioning until a long time of bug fixing.

Accomplishments that we're proud of

Successfully integrated multiple AI tools to create a realistic and interactive interviewing experience. Developed an intuitive, responsive, and clean UI that makes the interview practicing process simple and engaging

What we learned

How to orchestrate multiple APIs and services into a single cohesive application
Strategies for handling audio recording, transcription, and analysis efficiently in a frontend-backend workflow